Plateau lake digital ecological composite low-carbon value evaluation method and system

Abstract

The invention relates to the technical field of ecological evaluation, in particular to a plateau lake digital ecological composite low-carbon value evaluation method and system, and the method comprises the steps: determining a plurality of digital ecological monitoring points according to environment characteristic data, low-carbon attribute data and ecological protection-low-carbon cooperation requirements; and screening out a plurality of core monitoring points of the ecosystem service-composite low-carbon collaborative value from the plurality of digital ecological monitoring points according to a preset ecosystem service-composite low-carbon collaborative evaluation index and the human activity distribution condition of the area where the plateau lake is located. According to the invention, through the preset ecosystem service and low-carbon collaborative evaluation index, the ecological-low-carbon collaborative influence evaluation path can be generated, the influenced degree of the ecosystem service and the influenced degree of the low-carbon value are further evaluated, the collaborative values of different regions and different monitoring points can be refined, and the evaluation efficiency of the ecosystem service and the low-carbon value is improved. And the balance and influence between ecological protection and low carbon can be measured more comprehensively.

Description

Technical Field

[0001] This application relates to the field of ecological assessment technology, and in particular to a digital ecological composite low-carbon value assessment method and system for plateau lakes. Background Technology

[0002] Plateau lakes are lakes located in plateau regions, usually at high altitudes with significant topographic relief. Their formation is often related to geological processes such as crustal movement, glacial activity, river erosion, or volcanic activity.

[0003] Currently, traditional assessment methods rely on a limited number of monitoring sites, depending on conventional environmental data (such as climate data and basic water quality data), which can easily overlook more detailed ecological characteristics. This results in incomplete monitoring results, making it difficult to accurately reflect the spatial differences in ecosystem service value. Furthermore, the assessment areas of traditional methods are usually fixed and lack dynamic adjustment mechanisms, which may prevent timely optimization of the assessment area when the ecological environment changes.

[0004] Furthermore, traditional methods for assessing the value of ecosystem services often rely on a single dimension, such as a particular aspect of an ecosystem service (e.g., water quality or biodiversity), and cannot comprehensively assess the relationships and interactions between different ecosystem services. In addition, traditional methods lack precise support for ecological restoration, low-carbon development, and other initiatives. Due to the lack of detailed ecological monitoring and dynamic adjustments, they are unable to cope with the complexity and variability of the ecological environment. Summary of the Invention

[0005] The main purpose of this application is to provide a digital ecological composite low-carbon value assessment method and system for plateau lakes, so as to solve the problem of the relatively limited selection of monitoring points in the existing technology.

[0006] To achieve the above objectives, this application provides the following technical solution: A digital ecological composite low-carbon value assessment method for plateau lakes includes: Based on the geographical environment data and composite low-carbon correlation data of the plateau lakes, the ecologically sensitive areas and low-carbon key areas of the plateau lakes are identified. Obtain environmental characteristic data and low-carbon attribute data of the ecologically sensitive area, and determine several digital ecological monitoring points based on the environmental characteristic data, low-carbon attribute data and the requirements of ecological protection-low-carbon synergy; Based on the preset ecosystem service-compound low-carbon synergistic assessment indicators and the distribution of human activities in the area where the plateau lake is located, several core monitoring points for ecosystem service-compound low-carbon synergistic value are selected from several digital ecological monitoring points. Calculate the ecosystem service-composite low-carbon synergistic value index corresponding to each of the core monitoring points; based on the location information of several core monitoring points, take the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the center, use spatial interpolation method to generate the ecosystem service-composite low-carbon synergistic value assessment surface, and calculate the spatial coverage of the ecosystem service-composite low-carbon synergistic value assessment surface. When the spatial coverage is greater than or equal to the preset coverage threshold, the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index is determined as the main evaluation benchmark.

[0007] Preferably, based on geographical environmental data and composite low-carbon correlation data of the plateau lake area, the ecologically sensitive areas and low-carbon key areas of the plateau lake are identified, including: Based on the aforementioned geographical environment data and composite low-carbon correlation data, topographic and geomorphological data, land use data, and basic low-carbon attribute data are obtained within the plateau lake basin area. Using preset ecological sensitivity evaluation standards, low-carbon sensitivity evaluation standards, and minimum evaluation units as analysis conditions, spatial analysis methods are employed to comprehensively analyze the topographic data, land use data, and low-carbon attribute basic data to obtain ecologically sensitive areas and low-carbon key areas.

[0008] Preferably, environmental characteristic data and low-carbon attribute data of the ecologically sensitive area are acquired, and based on the environmental characteristic data, low-carbon attribute data, and the requirements for ecological protection-low-carbon synergy, several digital ecological monitoring points are determined, including: Based on the topographic data, land use data, and low-carbon attribute data, spatial interpolation methods are used to generate spatial distribution maps of environmental characteristics and low-carbon attributes for the ecologically sensitive areas and low-carbon key areas. The environmental characteristic data includes water quality parameters, biodiversity indicators, and vegetation cover, while the low-carbon attribute data includes soil carbon storage, water carbon flux, and vegetation carbon sequestration capacity. Based on the spatial distribution map of environmental characteristics and the spatial distribution map of low-carbon attributes, calculate the coefficient of variation of environmental characteristics, spatial autocorrelation index, coefficient of variation of low-carbon attributes, and low-carbon spatial correlation index within the ecologically sensitive area. Remote sensing image data, ecological vulnerability index, and low-carbon vulnerability index of the ecologically sensitive area and low-carbon key area are acquired, and normalized vegetation index and vegetation carbon sink potential index are calculated based on the remote sensing image data. Based on the environmental characteristic variation coefficient, the spatial autocorrelation index, the normalized vegetation index, the ecological vulnerability index, the low-carbon attribute variation coefficient, the low-carbon spatial correlation index, the vegetation carbon sink potential index, and the low-carbon vulnerability index, a monitoring site suitability evaluation matrix is ​​constructed, and the monitoring suitability score of different locations in the region is calculated. Based on the distribution of human activities, several digital ecological monitoring points that meet the requirements of ecological protection-low-carbon synergy are selected from several locations whose monitoring suitability scores are greater than or equal to the monitoring suitability score threshold. The requirements of ecological protection-low-carbon synergy include: the distance between the monitoring point and any source of human activity interference is greater than a preset protection distance; the carbon sink potential of the monitoring point is not less than a preset threshold; the distance between the monitoring point and the boundary of its adjacent ecologically sensitive area / low-carbon key area is within a preset reasonable range; and the spacing between the monitoring point and its adjacent monitoring points is greater than a preset monitoring spacing.

[0009] Preferably, based on preset ecosystem service-compound low-carbon synergistic assessment indicators and the distribution of human activities in the area where the plateau lake is located, several core monitoring points for ecosystem service-compound low-carbon synergistic value are selected from several digital ecological monitoring points, including: Based on the location information of several digital ecological monitoring points and the ecosystem service-composite low-carbon synergistic assessment indicators, an ecological-low-carbon synergistic impact assessment path is generated. Based on the preset assessment distance, obtain several assessment sampling points along the ecological-low-carbon synergistic impact assessment path; Based on the preset assessment radius and impact weight, an ecological-low-carbon synergistic impact assessment area is established at each of the assessment sampling points; Obtain the overlapping area between the ecological-low-carbon synergistic impact assessment area and the distribution of human activities, and determine the degree of impact on ecosystem services and the degree of impact on low-carbon value based on the overlapping area; Based on the degree of impact on ecosystem services, the degree of impact on low-carbon value, and the weight allocation of the ecosystem service-composite low-carbon synergistic assessment indicators corresponding to each of the aforementioned ecosystem-low-carbon synergistic impact assessment paths, the comprehensive index of ecosystem-low-carbon synergistic services corresponding to each of the aforementioned ecosystem-low-carbon synergistic impact assessment paths is determined. Based on the digital ecological monitoring points corresponding to each of the aforementioned ecological-low-carbon synergistic impact assessment paths, the comparison results between the ecological-low-carbon synergistic service comprehensive index and the preset ecological-low-carbon synergistic service index threshold are used to select core monitoring points from a number of digital ecological monitoring points; among them, the digital ecological monitoring points corresponding to the ecological-low-carbon synergistic impact assessment paths where the ecological-low-carbon synergistic service comprehensive index is greater than the ecological service index threshold are the core monitoring points.

[0010] Preferably, based on the location information of several digital ecological monitoring points and the ecosystem service-composite low-carbon synergistic assessment indicators, an ecological-low-carbon synergistic impact assessment path is generated, including: Based on the location information of several digital ecological monitoring points and the ecosystem service-composite low-carbon synergistic assessment index, a network analysis algorithm is used to generate an initial assessment path point sequence starting from each of the digital ecological monitoring points. Based on preset path intervals, curve smoothness, minimum turning angle and maximum slope limits, and low-carbon value continuity requirements, the initial assessment path point sequence is connected to generate an ecological-low-carbon synergistic impact assessment path.

[0011] Preferably, the ecosystem service-composite low-carbon synergistic value index corresponding to each of the core monitoring points is calculated, including: Based on each of the core monitoring points, the ecological-low-carbon collaborative assessment area of ​​the plateau lake is determined; the ecological-low-carbon collaborative assessment area is divided into several assessment grid units using a grid of preset size; Based on the type of ecosystem service in each assessment grid cell and the area of ​​each assessment grid cell, the ecosystem service density and low-carbon service density of each assessment grid cell are determined, and assessment grid cells with ecosystem service density and low-carbon service density greater than a preset density threshold are designated as key assessment areas. A radial assessment grid is established at the core monitoring points within the key assessment area, and several value assessment points are generated on the radial assessment grid. Based on the distribution of human activities, the service supply and demand relationship between the value assessment points and each assessment grid unit within the key assessment area is obtained, and several effective assessment points are selected from the several value assessment points. Based on the ecosystem service value, low-carbon value, and total number of the effective assessment points, determine the ecosystem service-composite low-carbon synergistic value index corresponding to each of the core monitoring points.

[0012] Preferably, based on the location information of several core monitoring points, and taking the core monitoring point with the highest current ecosystem service-compound low-carbon synergistic value index as the center, a spatial interpolation method is used to generate an ecosystem service-compound low-carbon synergistic value assessment surface, including: Based on the location information of several core monitoring points, taking the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the center, an initial ecosystem-low-carbon synergistic value point sequence is generated using a spatial interpolation method. Based on the preset spatial resolution, interpolation accuracy requirements, and low-carbon value interpolation priority, the value of each point in the initial ecological-low-carbon synergistic value point sequence is adjusted to obtain an optimized ecological-low-carbon synergistic value point sequence. Based on the preset spatial continuity constraints, interpolation radius, interpolation accuracy requirements, and low-carbon value spatial distribution constraints, the optimized ecological-low-carbon synergistic value point sequence is processed to obtain the ecosystem service-composite low-carbon synergistic value assessment surface.

[0013] Preferably, the spatial coverage of the ecosystem service-complex low-carbon synergistic value assessment surface is calculated, including: Based on the location information of several core monitoring points, the scope of the ecological-low-carbon collaborative assessment of the plateau lake is determined; Based on the preset assessment accuracy and ecological-low-carbon value stratification standard, several value level regions corresponding to the ecosystem service-composite low-carbon synergistic value assessment surface are generated. Based on the location information of each value level region, the preset assessment credibility threshold and the low-carbon assessment credibility threshold, the effective assessment area corresponding to the ecosystem service-composite low-carbon synergistic value assessment surface is determined. The spatial coverage of the ecosystem service-composite low-carbon synergistic value assessment surface is obtained by comparing the area of ​​the overlapping area between the effective assessment area and the ecological-low-carbon synergistic assessment range with the area of ​​the ecological-low-carbon synergistic assessment range.

[0014] Preferably, the method further includes: When the spatial coverage is less than the preset coverage threshold, the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index will be removed. A new ecosystem service-composite low-carbon synergistic value assessment surface is generated, centered on the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index. The spatial coverage of the new ecosystem service-composite low-carbon synergistic value assessment surface is calculated until the spatial coverage meets the coverage threshold.

[0015] To achieve the above objectives, this application also provides the following technical solution: a digital ecological composite low-carbon value assessment system for plateau lakes, applicable to the aforementioned digital ecological composite low-carbon value assessment method for plateau lakes, comprising: The data identification module is used to identify the ecologically sensitive areas and low-carbon key areas of the plateau lakes based on the geographical environment data and composite low-carbon correlation data of the plateau lake area. The location determination module is used to acquire environmental characteristic data and low-carbon attribute data of the ecologically sensitive area, and determine several digital ecological monitoring locations based on the environmental characteristic data, low-carbon attribute data and ecological protection-low-carbon synergy requirements. The site selection module is used to select several core monitoring sites with ecosystem service-composite low-carbon synergy value from several digital ecological monitoring sites based on preset ecosystem service-composite low-carbon synergy assessment indicators and the distribution of human activities in the area where the plateau lake is located. The value assessment module is used to calculate the ecosystem service-composite low-carbon synergistic value index corresponding to each of the core monitoring points; based on the location information of several core monitoring points, taking the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the center, the module uses a spatial interpolation method to generate an ecosystem service-composite low-carbon synergistic value assessment surface, and calculates the spatial coverage of the ecosystem service-composite low-carbon synergistic value assessment surface. The location determination module is used to determine the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the main evaluation benchmark point when the spatial coverage is greater than or equal to a preset coverage threshold.

[0016] (1) This application can intelligently select the most suitable digital ecological monitoring points by comprehensively considering environmental characteristics, low-carbon attribute data and ecological protection and low-carbon synergy requirements. It can effectively monitor the interaction between the ecosystem and low-carbon attributes and promptly discover potential ecologically vulnerable areas. Furthermore, by using spatial interpolation methods to generate an ecosystem service-composite low-carbon synergy value assessment surface and optimizing it according to spatial continuity and low-carbon value interpolation priority, it can ensure that the spatial distribution of the assessment surface is accurate and reliable, reflecting the spatial change trend of the actual ecological and low-carbon synergy value. (2) This application can generate an ecological-low-carbon synergistic impact assessment path based on the preset ecosystem service and low-carbon synergistic assessment indicators, and further assess the impact of ecosystem services and low-carbon value. It can refine the synergistic value of different regions and monitoring points, and more comprehensively measure the balance and impact between ecological protection and low carbon. (3) By calculating the spatial coverage of the ecosystem service-composite low-carbon synergistic value assessment surface, this application can dynamically determine whether the preset coverage threshold is met, thereby deciding whether the assessment strategy needs to be adjusted, ensuring the high credibility and accuracy of the final assessment results, and avoiding the limitation of over-reliance on a single data point; and through multi-dimensional assessment, it can comprehensively assess the service value of the ecosystem, providing a scientific basis for ecological restoration, low-carbon development and sustainable management. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the steps in one embodiment of the digital ecological composite low-carbon value assessment method for plateau lakes according to this application; Figure 2 This is a schematic diagram of the system architecture of an embodiment of a digital ecological composite low-carbon value assessment system for plateau lakes according to this application.

[0018] Attached reference numerals: 1. Data recognition module; 2. Location determination module; 3. Location screening module; 4. Value assessment module; 5. Location judgment module. Detailed Implementation

[0019] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0020] like Figure 1 As shown, the present invention proposes a digital ecological composite low-carbon value assessment method for plateau lakes, comprising: S1. Based on the geographical environment data and composite low-carbon correlation data of the plateau lake area, identify the ecologically sensitive areas and low-carbon key areas of the plateau lake. S2. Obtain environmental characteristic data and low-carbon attribute data of ecologically sensitive areas, and determine several digital ecological monitoring points based on the environmental characteristic data, low-carbon attribute data and the requirements of ecological protection-low-carbon synergy. S3. Based on the preset ecosystem service-compound low-carbon synergistic assessment indicators and the distribution of human activities in the plateau lake area, select several core monitoring points for ecosystem service-compound low-carbon synergistic value from several digital ecological monitoring points. S4. Calculate the ecosystem service-composite low-carbon synergistic value index corresponding to each core monitoring point; based on the location information of several core monitoring points, take the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the center, use spatial interpolation method to generate the ecosystem service-composite low-carbon synergistic value assessment surface, and calculate the spatial coverage of the ecosystem service-composite low-carbon synergistic value assessment surface. S5. When the spatial coverage is greater than or equal to the preset coverage threshold, the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index shall be determined as the main evaluation benchmark.

[0021] It should be noted that the geographical environmental data of the plateau lake area includes environmental characteristics such as climate, topography, and hydrology. This data helps identify ecologically sensitive areas (such as ecologically fragile areas) and key low-carbon areas (low-carbon emission areas or low-carbon technology application areas) around the plateau lakes. Composite low-carbon related data refers to data related to low-carbon emissions, carbon absorption, and the use of low-carbon technologies in the region. Combined with environmental characteristics, this helps determine which areas require key protection or monitoring. Various environmental data (such as soil quality, vegetation cover, etc.) and low-carbon related data (such as carbon emissions, carbon storage, etc.) are collected. Considering the synergistic relationship between ecological protection and low-carbon goals, core areas that need to be monitored are proposed, and several digital ecological monitoring points are identified. These points will be used to collect real-time data for further analysis. The ecosystem service-composite low-carbon synergistic assessment index is a multi-dimensional evaluation standard that measures the synergistic effect of ecosystem services (such as water purification, carbon absorption, etc.) and low-carbon effects. It combines the impact of human activities (such as agriculture, industry, tourism, etc.) on the ecological environment. By assessing the importance of monitoring points in ecosystem services and low-carbon synergy, several of the most representative monitoring points are selected. These points can help further evaluate the overall ecological and low-carbon performance of the region. For each core monitoring point, a comprehensive value index is calculated based on its ecosystem services (such as biodiversity and carbon storage) and low-carbon benefits (such as carbon emission reduction and energy efficiency). This index represents the degree of integration between the ecological value and low-carbon benefits of that point. Based on the value indices of each core monitoring point, the data of these points are extended to the entire region using spatial interpolation methods (such as Kriging interpolation) to generate a continuous ecosystem service-composite low-carbon synergy value assessment surface, representing the distribution of ecological and low-carbon values ​​at different locations within the region. The extent of the coverage area of ​​this assessment surface is evaluated to obtain the spatial distribution of ecosystem service and low-carbon synergy values ​​in the region. If the spatial coverage is greater than or equal to a preset coverage threshold, it indicates that the area centered on this core monitoring point has sufficient ecological and low-carbon value and meets the assessment criteria. This core monitoring point is then the main assessment benchmark and can be used as the assessment benchmark for the region's ecological protection and low-carbon goals.

[0022] In an optional embodiment, based on geographical environmental data and composite low-carbon correlation data of the plateau lake area, ecologically sensitive areas and low-carbon key areas of the plateau lake are identified, including: Based on geographical environment data and composite low-carbon correlation data, topographic and geomorphological data, land use data and basic data on low-carbon attributes within the plateau lake basin are obtained; Using preset ecological sensitivity evaluation standards, low-carbon sensitivity evaluation standards, and minimum evaluation units as analysis conditions, spatial analysis methods are employed to comprehensively analyze topographic data, land use data, and basic low-carbon attribute data to identify ecologically sensitive areas and key low-carbon areas.

[0023] It should be noted that topographic and geomorphological data includes information such as the region's topography, slope, altitude, and river distribution. This data helps in understanding the region's natural environment and physical characteristics. For example, hills, mountains, and low-lying areas in certain plateau regions may have different impacts on ecosystems, affecting hydrological and ecological processes. Land use data refers to the region's land use types, including agriculture, forestry, urbanization, and other land uses. Land use patterns directly affect the ecological environment and low-carbon attributes; for example, overdeveloped land may reduce carbon storage and water conservation. Basic data on low-carbon attributes includes the region's carbon emissions, carbon absorption capacity, renewable energy usage, and energy... Data such as consumption patterns help understand the low-carbon benefits of a region and assess the low-carbon sensitivity of different regions. Ecological sensitivity assessment criteria are used to measure the ecological vulnerability of a region. For example, some regions may have high ecological sensitivity due to rich biodiversity or important water resources. The criteria may consider aspects such as biological habitats, wetland area, and species protection. Low-carbon sensitivity assessment criteria are used to assess the low-carbon vulnerability of a region. For example, regions with high carbon emissions or low carbon storage may be considered low-carbon sensitive, meaning they are more dependent on low-carbon measures. The criteria may include factors such as carbon footprint, energy structure, and the proportion of renewable energy. The smallest evaluation unit is a small regional unit (such as a grid, a small plot of land, or an administrative division) used for data analysis and evaluation. These units form the basis of the analysis, used to spatially divide and classify data. Spatial analysis methods are used to combine different types of data (such as topography, land use, and low-carbon attributes) for analysis using Geographic Information System (GIS) tools. For example, techniques such as spatial overlay, buffer analysis, and cluster analysis are used to comprehensively process data at multiple levels, revealing the ecological and low-carbon sensitivities within a region. By comprehensively analyzing data such as topography, land use, and low-carbon attributes, it is possible to identify which areas are particularly important for ecological protection and which areas require more attention during the low-carbon transition. For example, some mountainous areas may be ecologically sensitive areas, while some urbanized areas may be low-carbon sensitive areas. Ecologically sensitive areas possess important natural resources, unique biological habitats, or significant hydrological functions. Based on ecological sensitivity standards, certain areas within these regions may be designated as ecologically sensitive, meaning they require special protection measures. These areas may contribute significantly to ecosystem services, such as water conservation and air purification. Low-carbon critical areas play a crucial role in low-carbon emissions and carbon absorption. Low-carbon critical areas typically require specific policies and measures to optimize carbon emissions and enhance carbon sequestration capacity. These areas may be forests or grasslands with large carbon reserves, or regions with the potential to develop renewable energy.

[0024] In an optional embodiment, environmental characteristic data and low-carbon attribute data of ecologically sensitive areas are acquired. Based on the environmental characteristic data, low-carbon attribute data, and the requirements for ecological protection-low-carbon synergy, several digital ecological monitoring points are determined, including: Based on topographic data, land use data, and basic data on low-carbon attributes, spatial interpolation methods are used to generate spatial distribution maps of environmental characteristics and low-carbon attributes for ecologically sensitive areas and key low-carbon areas. Among them, environmental characteristic data includes water quality parameters, biodiversity indicators, vegetation cover, etc., and low-carbon attribute data includes soil carbon storage, water carbon flux, vegetation carbon sequestration capacity, etc. Based on the spatial distribution map of environmental characteristics and the spatial distribution map of low-carbon attributes, calculate the coefficient of variation of environmental characteristics, spatial autocorrelation index, coefficient of variation of low-carbon attributes, and low-carbon spatial correlation index within the ecologically sensitive area. Acquire remote sensing image data, ecological vulnerability index, and low-carbon vulnerability index of ecologically sensitive areas and key low-carbon areas, and calculate normalized vegetation index and vegetation carbon sink potential index based on remote sensing image data; Based on the environmental characteristic variation coefficient, spatial autocorrelation index, normalized vegetation index, ecological vulnerability index, low-carbon attribute variation coefficient, low-carbon spatial correlation index, vegetation carbon sink potential index, and low-carbon vulnerability index, a monitoring site suitability evaluation matrix is ​​constructed, and the monitoring suitability score of different locations in the region is calculated. The formula for calculating the monitoring suitability score is as follows; ; in, (Normalization of positive indicators); If it is a negative indicator, then ; in, Indicates the first The monitoring suitability score for each location, Indicates the evaluation indicator number. Indicates the first The weight of each evaluation indicator, Indicates the first The position The normalized value of each indicator. Indicates the first The position The original values ​​of each indicator Indicates the first The maximum value of each indicator within the evaluation area. Indicates the first The minimum value of each indicator within the evaluation area; Based on the distribution of human activities, several digital ecological monitoring sites that meet the requirements of ecological protection-low-carbon synergy are selected from several locations whose monitoring suitability scores are greater than or equal to the monitoring suitability score threshold. Among them, the requirements of ecological protection-low-carbon synergy include that the distance between the monitoring site and any source of human activity disturbance is greater than the preset protection distance, the carbon sink potential of the monitoring site is not lower than the preset threshold, the distance between the monitoring site and the boundary of the adjacent ecologically sensitive area / low-carbon key area is within the preset reasonable range, and the spacing between the monitoring site and the adjacent monitoring sites is greater than the preset monitoring spacing.

[0025] It should be noted that spatial interpolation is a technique for extrapolating data from unobserved points using known data points. In this process, based on existing data such as topography, land use, and low-carbon attributes, spatial interpolation methods can generate spatial distribution maps of different characteristics within a region. Environmental characteristic data includes water quality parameters (such as pH and dissolved oxygen), biodiversity indicators (such as species abundance and habitat quality), and vegetation cover (the extent of plant growth). Through spatial interpolation, spatial distribution maps of these environmental characteristics can be generated, helping to identify which areas have a good ecological environment and which areas may face ecological threats. Low-carbon attribute data includes soil carbon storage (moisture content and organic matter content), water carbon flux (the absorption and release of carbon by water bodies), and vegetation carbon sequestration capacity (the ability of plants to absorb carbon dioxide). Similarly, through spatial interpolation, spatial distribution maps of low-carbon attributes within a region can be obtained, revealing which areas have high carbon sequestration potential and which areas may require strengthened low-carbon management. The coefficient of variation (COP) of environmental characteristics measures the spatial variability of environmental characteristics (such as water quality and vegetation cover). A larger COP indicates a more uneven spatial distribution of the characteristic, which may indicate the instability of the regional ecosystem. The spatial autocorrelation index measures the similarity of environmental characteristics or low-carbon attributes between adjacent locations within a region. High autocorrelation indicates strong similarity in environmental or low-carbon characteristics within the region, while low autocorrelation indicates significant differences in characteristic distribution. The COP and low-carbon spatial correlation index are used to assess the distribution variation of low-carbon attributes (such as carbon storage and carbon flux) and the spatial correlation of these low-carbon characteristics. Remote sensing data, such as satellite imagery, is used to obtain the actual environmental data of the region. Environmental information, especially vegetation cover and land use; the Normalized Difference Vegetation Index (NDVI) is a commonly used remote sensing index to measure vegetation growth status; a high NDVI value usually indicates vigorous plant growth and strong carbon fixation capacity; the vegetation carbon sink potential index reflects the vegetation's ability to absorb and fix carbon; it combines vegetation cover and growth status to help assess the contribution of vegetation to carbon sinks in a certain area; the ecological vulnerability index and the low-carbon vulnerability index assess the vulnerability of ecosystems and low-carbon systems, respectively, revealing potential ecological environment or low-carbon problems; for example, areas with high ecological vulnerability may need to strengthen protection measures, while areas with high low-carbon vulnerability may need to adopt more low-carbon management strategies; Based on the aforementioned spatial distribution map and various indices, a monitoring site suitability evaluation matrix is ​​constructed to assess the suitability of different locations as monitoring sites. Each potential monitoring site is scored by calculating a comprehensive score based on environmental and low-carbon characteristics. A suitability score for each monitoring site is calculated based on the evaluation criteria in the matrix. These scores reflect the importance and suitability of a location in ecological monitoring and low-carbon management. When selecting suitable monitoring sites, multiple factors need to be considered to ensure that the monitoring sites can effectively monitor ecological protection and contribute to low-carbon management. Specific requirements include: monitoring sites should be far from areas with dense human activity to reduce the impact of human interference on the data; selected monitoring sites must have high carbon sequestration potential, i.e., their vegetation carbon sequestration capacity must not be lower than a set threshold; monitoring sites should be close to ecologically sensitive areas or key low-carbon areas to ensure that monitoring can cover important ecological and low-carbon areas; and there should be a reasonable distance between selected monitoring sites to avoid overly dense monitoring coverage that could affect data accuracy.

[0026] In an optional embodiment, based on preset ecosystem service-compound low-carbon synergistic assessment indicators and the distribution of human activities in the area where the plateau lake is located, several core monitoring points for ecosystem service-compound low-carbon synergistic value are selected from several digital ecological monitoring points, including: Based on the location information of several digital ecological monitoring points and the ecosystem service-composite low-carbon synergistic assessment indicators, an ecological-low-carbon synergistic impact assessment path is generated. Based on the preset assessment distance, obtain several assessment sampling points along the ecological-low-carbon synergistic impact assessment path; Based on the preset assessment radius and impact weight, an assessment area for the synergistic impact of ecology and low carbon is established at each assessment sampling point; Obtain the overlapping areas between the ecological-low-carbon synergistic impact assessment area and the distribution of human activities, and determine the degree of impact on ecosystem services and low-carbon value based on the overlapping areas; Based on the weight allocation of the ecological service impact degree, low-carbon value impact degree, and ecosystem service-composite low-carbon synergistic assessment indicators corresponding to each ecological-low-carbon synergistic impact assessment path, the comprehensive ecological-low-carbon synergistic service index corresponding to each ecological-low-carbon synergistic impact assessment path is determined. Based on the digital ecological monitoring points corresponding to each ecological-low-carbon synergistic impact assessment path, the comparison results between the comprehensive ecological-low-carbon synergistic service index and the preset ecological-low-carbon synergistic service index threshold are used to select core monitoring points from several digital ecological monitoring points; among them, the digital ecological monitoring points corresponding to the ecological-low-carbon synergistic impact assessment path where the comprehensive ecological-low-carbon synergistic service index is greater than the ecological service index threshold are the core monitoring points.

[0027] It is important to note that, to ensure the comprehensiveness of the assessment, an assessment scope needs to be defined, based on a pre-set assessment distance. Multiple sampling points along the assessment path will be distributed along this distance. These sampling points are used to collect data and calculate the impacts on ecological and low-carbon systems. Each sampling point represents a specific environmental location and will serve as the basis for subsequent assessments. The impact range of each sampling point will be determined based on the assessment radius, and the degree of impact (e.g., ecological impact and low-carbon impact) in different areas will have different weights. For example, areas near water bodies or forests may have a higher ecological or carbon sink impact. At each sampling point, an impact assessment area is defined based on the impact radius and weights. The size and importance of this area depend on the degree of interaction between the ecological and low-carbon systems. Within this area, human activities (such as urban construction, agriculture, and industry) will have varying degrees of impact on the ecological and low-carbon systems. By analyzing the spatial distribution of these activities, we can understand their overlap with the assessment area. Through the overlapping areas, we can assess the impact of human activities on ecosystem services and low-carbon value. If the overlapping area is large, it indicates that human activities have a greater impact on the ecosystem services and low-carbon value of the area, and vice versa. Within each assessment area, the impact on ecosystem services and low-carbon value needs to be evaluated. This typically includes changes in ecological functions (such as water quality improvement and air purification) and carbon storage. By integrating various impact indicators (such as ecosystem services, low-carbon value, and other synergistic assessment indicators), a comprehensive service index is calculated for each ecosystem-low-carbon synergistic impact assessment path. This comprehensive index reflects the overall ecosystem-low-carbon benefits of the path. The comprehensive ecosystem-low-carbon synergistic service indices of all assessment paths are compared with a preset "ecosystem-low-carbon synergistic service index threshold." The digital ecological monitoring points corresponding to those paths whose comprehensive indices exceed the threshold are considered core monitoring points. Core monitoring points typically have high ecosystem and low-carbon service value and are the focus of monitoring and management.

[0028] In an optional embodiment, based on the location information of several digital ecological monitoring points and ecosystem service-composite low-carbon synergistic assessment indicators, an ecological-low-carbon synergistic impact assessment path is generated, including: Based on the location information of several digital ecological monitoring points and the ecosystem service-composite low-carbon synergistic assessment index, a network analysis algorithm is used to generate an initial assessment path point sequence starting from each digital ecological monitoring point. Based on preset path intervals, curve smoothness, minimum turning angle and maximum slope limits, and low-carbon value continuity requirements, the initial assessment path point sequence is connected to generate an ecological-low-carbon synergistic impact assessment path.

[0029] It should be noted that network analysis algorithms are typically used to find the optimal path between known nodes (such as monitoring points). Here, the network analysis algorithm generates a preliminary path sequence based on the location information of each monitoring point and relevant evaluation indicators. This path sequence connects all monitoring points, forming a preliminary evaluation path. To ensure the effectiveness and representativeness of the path, an appropriate path interval needs to be set. The path interval determines the distance between every two sampling points during the evaluation process. For example, if the path interval is too large, it may not be able to effectively capture certain details; if the interval is too small, it may cause data redundancy. In path planning, overly curved paths may affect the accuracy of the evaluation, so the smoothness of the path needs to be controlled. The path should avoid large bends as much as possible to ensure the continuity of the evaluation process and the availability of data. The size of the turning angle affects the stability and feasibility of the path. Presetting a minimum turning angle is to avoid overly sharp turns in the path and ensure the feasibility of the path under terrain or other natural obstacles. In some areas, the path may traverse mountains or other sloping terrain; therefore, setting a maximum slope limit is very important to ensure the operability and practical application of the path. This can prevent the path from becoming infeasible or dangerous due to excessive slope. When planning the route, the continuity of the low-carbon system must be considered, i.e., the route should avoid traversing areas with high carbon emissions or weak carbon absorption capacity. The route design must ensure good continuity of low-carbon value along the way, avoiding interruptions or decline. After meeting all the above constraints, the algorithm will optimize and connect these route points to generate the final ecological-low-carbon synergistic impact assessment route. This assessment route not only considers the synergistic effects of ecological and low-carbon goals but also ensures the feasibility and effectiveness of the route: each point on the assessment route represents a key location that can be used to analyze the spatial interaction between ecological and low-carbon systems. Through this route, the impact of different route segments on ecosystem services and low-carbon value can be further analyzed, helping to more accurately assess and optimize relevant policies or action plans.

[0030] In an optional embodiment, the ecosystem service-composite low-carbon synergistic value index corresponding to each core monitoring point is calculated, including: Based on each core monitoring point, the ecological-low-carbon collaborative assessment area of ​​the plateau lake was determined; the ecological-low-carbon collaborative assessment area was divided into several assessment grid units using a grid of preset size. Based on the type of ecosystem services in each assessment grid unit and the area of ​​each assessment grid unit, the ecosystem service density and low-carbon service density of each assessment grid unit are determined, and assessment grid units with ecosystem service density and low-carbon service density greater than the preset density threshold are designated as key assessment areas. A radial assessment grid is established at the core monitoring points in the key assessment area, and several value assessment points are generated on the radial assessment grid. Based on the distribution of human activities, the service supply and demand relationship between the value assessment points in the key assessment area and each assessment grid unit is obtained, and several effective assessment points are selected from the several value assessment points. Based on the ecosystem service value, low-carbon value, and total number of value assessment points at the effective assessment points, determine the ecosystem service-composite low-carbon synergistic value index corresponding to each core monitoring point. The calculation formula for the ecosystem service-composite low-carbon synergistic value index is as follows; ; in, Indicates the first The collaborative value index of each core monitoring point The synergistic weights representing the value of ecosystem services Indicates the first The number of valid assessment points corresponding to each core monitoring point Indicates the first The first core monitoring point The ecosystem service value of an effective assessment point Indicates the first The first core monitoring point The low-carbon value of each effective assessment point.

[0031] It should be noted that core monitoring points are known key monitoring locations, which may be the central points for research or data collection. The distribution of these monitoring points determines an overall assessment area, namely the ecological-low-carbon synergistic assessment area for plateau lakes. These areas are used to analyze the interaction and impact between the ecosystem and low-carbon measures. Based on the size of the assessment area and the required analytical precision, the entire ecological-low-carbon synergistic assessment area is divided into several grid units. Each grid unit represents a smaller area, and the size of these grids is pre-defined to facilitate independent analysis of each smaller unit. Each grid unit has the same size and shape, allowing for uniform quantitative analysis of the area. Different types of ecosystem services exist within each grid unit, such as water source protection, carbon absorption, and biodiversity conservation. These ecosystem service types affect the environmental quality and function of the area. In addition to ecosystem services, low-carbon service density, such as forest carbon storage and vegetation cover, is also considered, as these factors directly affect the capacity for carbon emission reduction and carbon absorption. By setting a density threshold for ecological and low-carbon services, grid units with high density of ecological and low-carbon services are selected. These grid units will be marked as key assessment areas because they play an important role in ecological protection and low-carbon goals. Within these high-density areas, core monitoring points are the focus of the analysis, and a radial assessment grid is established around these points. This radial design allows for better coverage and analysis of the surrounding areas. On the radial grid, several value assessment points are generated based on different environmental characteristics and service needs. These points represent the specific performance of ecological and low-carbon services within the region. Based on the distribution of human activities, the supply and demand relationship of ecological and low-carbon services between each value assessment point and each grid unit is analyzed. This helps identify which areas provide sufficient ecological and low-carbon services and which areas have demand gaps or insufficient services. From multiple value assessment points, effective assessment points that truly reflect the synergistic effect of ecological and low-carbon services are selected. Effective assessment points are those that truly reflect the ecological and low-carbon value of the region. Each valid assessment point has its specific ecosystem service value and low-carbon value. This value is based on the previous analysis results and takes into account the importance of each assessment point in ecosystem services and low-carbon goals. After assessing the total number of these valid assessment points, the ecosystem service-composite low-carbon synergistic value index corresponding to each core monitoring point can be obtained. This index is a comprehensive indicator that measures the synergistic effect of ecological and low-carbon services in a certain region and reflects the region's comprehensive performance in ecological protection and low-carbon emission reduction.

[0032] In an optional embodiment, based on the location information of several core monitoring points, and taking the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the center, a spatial interpolation method is used to generate an ecosystem service-composite low-carbon synergistic value assessment surface, including: Based on the location information of several core monitoring points, taking the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the center, an initial ecosystem-low-carbon synergistic value point sequence is generated using spatial interpolation method; Based on the preset spatial resolution, interpolation accuracy requirements and low-carbon value interpolation priority, the value of each point in the initial ecological-low-carbon synergistic value point sequence is adjusted to obtain the optimized ecological-low-carbon synergistic value point sequence. Based on the preset spatial continuity constraints, interpolation radius, interpolation accuracy requirements, and low-carbon value spatial distribution constraints, the optimized ecological-low-carbon synergistic value point sequence is processed to obtain the ecosystem service-composite low-carbon synergistic value assessment surface.

[0033] It should be noted that, based on the ecological-low-carbon synergistic value index of each core monitoring point, the point with the highest value is first selected as the center; this point represents the optimal state of the current regional ecological and low-carbon synergistic effect. Using spatial interpolation technology, starting from the center point, the value information of this point is extended to the surrounding area to generate a preliminary value point sequence. These points will represent the ecological and low-carbon synergistic effect at different locations in the region. The interpolation process is based on the values ​​of the core monitoring points to make spatial inferences and fill in areas not directly monitored. In practice, spatial resolution indicates the granularity of the data output; the higher the resolution, the more detailed the result. Interpolation accuracy requirements refer to the accuracy requirements of the values ​​during the interpolation process, that is, the values ​​of the generated ecological-low-carbon value points must meet a certain accuracy standard. During the interpolation process, low-carbon value (such as carbon storage or emission reduction benefits) may be given higher priority; this means that when generating the value point sequence, the interpolation of low-carbon benefits will be given priority or emphasized to ensure that the spatial distribution of low-carbon services is accurately reflected. Based on these requirements, the points in the initial ecological-low-carbon synergistic value point sequence are adjusted to better meet the preset accuracy requirements and priorities. After adjustment, an optimized point sequence is obtained, which more accurately reflects the ecological and low-carbon value of the entire assessment area. Spatial continuity constraints require that the changes between adjacent value points be smooth, avoiding unreasonable jumps or abrupt changes. This means that the generated ecological-low-carbon synergistic value distribution should exhibit a certain degree of coherence and spatial logic. The interpolation radius refers to the range of neighboring points considered when generating each new point; a larger radius will involve more surrounding points, while a smaller radius will focus on local areas. The interpolation accuracy should be... The criteria ensure that the values ​​for the entire region meet expectations at the detailed level; the spatial distribution constraints of low-carbon value ensure that the distribution of low-carbon benefits within the entire assessment area conforms to the preset logic, such as the reasonable representation of the distribution of areas with high low-carbon service efficiency, avoiding the appearance of areas with excessively low low-carbon service density; based on the adjusted and optimized point sequence, a comprehensive "ecological-low-carbon synergistic value assessment surface" is finally generated through spatial interpolation methods; this assessment surface is a continuous spatial distribution map that reflects the comprehensive value of ecosystem services and low-carbon benefits at different locations within the entire region; it not only considers the specific value of each point, but also reflects the spatial relationships between regions and the synergistic effect of ecology and low-carbon.

[0034] In an optional embodiment, calculating the spatial coverage of the ecosystem services-complex low-carbon synergistic value assessment surface includes: Based on the location information of several core monitoring points, the scope of the ecological-low-carbon collaborative assessment of plateau lakes was determined; Based on the preset assessment accuracy and ecological-low-carbon value stratification standards, several value level regions corresponding to the ecosystem service-composite low-carbon synergistic value assessment surface are generated. Based on the location information of each value level area, the preset assessment credibility threshold and the low-carbon assessment credibility threshold, the effective assessment area corresponding to the ecosystem service-composite low-carbon synergistic value assessment surface is determined. The spatial coverage of the ecosystem service-complex low-carbon synergistic value assessment surface is obtained by comparing the area of ​​the overlapping area between the effective assessment area and the ecological-low-carbon synergistic assessment scope with the area of ​​the ecological-low-carbon synergistic assessment scope.

[0035] It should be noted that by collecting information from several core monitoring points, the scope of the ecological-low-carbon synergistic assessment of plateau lakes is determined. These monitoring points are known key locations, representing important nodes for ecological and low-carbon services. Based on these locations, a spatial range can be inferred, covering the ecosystem services and low-carbon benefits that need to be assessed within the region. Next, according to the preset assessment accuracy and ecological-low-carbon value stratification standards, the assessment area is divided into different value level regions. These standards determine the level of ecological and low-carbon synergistic services in each region, usually classified according to the actual performance of each region (such as carbon storage, ecosystem service benefits, etc.). Through these standards, the entire region can be divided into multiple levels, reflecting the ecological-low-carbon synergistic benefits of different regions. After identifying regions with different value levels, it is necessary to further screen out "effective assessment regions." Effective assessment regions refer to those areas that have high credibility during the assessment process and meet the preset assessment criteria. Assessment credibility thresholds and low-carbon assessment credibility thresholds are used to determine which regions' assessment results are reliable. Only when a region's assessment value exceeds these thresholds is it considered an effective assessment region. Finally, the assessment coverage is calculated by comparing the overlapping area between the effective assessment regions and the initially determined ecological-low-carbon collaborative assessment scope with the area of ​​the entire assessment scope. The overlapping area represents the portion where the effective assessment regions intersect with the assessment scope, while the total area of ​​the assessment scope represents the total assessment area of ​​that region. By calculating the ratio of these two, the final spatial coverage is obtained, which represents the proportion of effective assessment regions in the entire assessment scope, helping to understand the spatial representativeness and effectiveness of the assessment results.

[0036] In an optional embodiment, the method further includes: When the spatial coverage is less than the preset coverage threshold, the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index will be removed. A new ecosystem service-composite low-carbon synergistic value assessment surface is generated, centered on the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index. The spatial coverage of the new ecosystem service-composite low-carbon synergistic value assessment surface is calculated until the spatial coverage meets the coverage threshold.

[0037] It should be noted that the system calculates the spatial coverage of the current assessment surface; this is an indicator that measures the actual coverage of the assessment area. If the current spatial coverage is less than a preset threshold, it means that the spatial coverage of the assessment results is not comprehensive or accurate enough, and cannot meet the requirements. When insufficient spatial coverage is detected, the system will take measures to remove a key core monitoring point. Specifically, this monitoring point is the point with the highest ecosystem service and low-carbon synergy value index in the current assessment surface. This point usually represents the extreme value of the ecological and low-carbon synergy benefits in the area, but if it is too prominent or too concentrated, it may lead to insufficient coverage of the assessment surface. Removing this point is to readjust the assessment surface and improve the spatial coverage. Once the highest-value monitoring point is removed, the system will generate a new ecosystem service-composite low-carbon synergistic value assessment surface, centered on the remaining highest-value core monitoring point. This means the assessment area will be readjusted to ensure that the new assessment surface covers the area more evenly and extensively in space. After generating the new assessment surface, the system will recalculate the new spatial coverage. In this way, the assessment surface may be expanded or rearranged to ensure more comprehensive coverage of the entire plateau lake area. This process will continue until the new assessment surface reaches the preset spatial coverage threshold. If the spatial coverage of the newly generated assessment surface is still insufficient, the system will continue to remove core monitoring points and regenerate assessment surfaces until the requirements are met.

[0038] like Figure 2 As shown, the present invention proposes a digital ecological composite low-carbon value assessment system for plateau lakes, which is applicable to the aforementioned digital ecological composite low-carbon value assessment method for plateau lakes, comprising: Data identification module 1 is used to identify ecologically sensitive areas and key low-carbon areas of plateau lakes based on geographical environmental data and composite low-carbon correlation data of the plateau lake area. The location determination module 2 is used to acquire environmental characteristic data and low-carbon attribute data of ecologically sensitive areas, and determine several digital ecological monitoring locations based on the environmental characteristic data, low-carbon attribute data and the requirements of ecological protection-low-carbon synergy. The site selection module 3 is used to select several core monitoring sites for the synergistic value of ecosystem services and low carbon based on preset ecosystem service-composite low carbon synergy assessment indicators and the distribution of human activities in the area where the plateau lake is located. Value assessment module 4 is used to calculate the ecosystem service-composite low-carbon synergistic value index corresponding to each core monitoring point; based on the location information of several core monitoring points, taking the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the center, a spatial interpolation method is used to generate an ecosystem service-composite low-carbon synergistic value assessment surface, and calculate the spatial coverage of the ecosystem service-composite low-carbon synergistic value assessment surface. The location determination module 5 is used to determine the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the main evaluation benchmark point when the spatial coverage is greater than or equal to the preset coverage threshold.

[0039] The specific embodiments of the invention have been described in detail above, but they are only examples, and this application is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modifications or substitutions to the invention are also within the scope of this application. Therefore, all equivalent changes, modifications, and improvements made without departing from the spirit and principles of this application should be covered within the scope of this application.

Claims

1. A method for assessing the digital ecological composite low-carbon value of plateau lakes, characterized in that, include: Based on the geographical environment data and composite low-carbon correlation data of the plateau lakes, the ecologically sensitive areas and low-carbon key areas of the plateau lakes are identified. Obtain environmental characteristic data and low-carbon attribute data of the ecologically sensitive area, and determine several digital ecological monitoring points based on the environmental characteristic data, low-carbon attribute data and the requirements of ecological protection-low-carbon synergy. Based on the preset ecosystem service-compound low-carbon synergistic assessment indicators and the distribution of human activities in the area where the plateau lake is located, several core monitoring points for ecosystem service-compound low-carbon synergistic value are selected from several digital ecological monitoring points. Calculate the ecosystem service-composite low-carbon synergistic value index corresponding to each of the core monitoring points; based on the location information of several core monitoring points, take the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the center, use spatial interpolation method to generate the ecosystem service-composite low-carbon synergistic value assessment surface, and calculate the spatial coverage of the ecosystem service-composite low-carbon synergistic value assessment surface. When the spatial coverage is greater than or equal to the preset coverage threshold, the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index is determined as the main evaluation benchmark.

2. The method for assessing the digital ecological composite low-carbon value of plateau lakes according to claim 1, characterized in that, Based on geographical environmental data and composite low-carbon correlation data of the plateau lakes' locations, ecologically sensitive areas and key low-carbon areas of the plateau lakes are identified, including: Based on the aforementioned geographical environment data and composite low-carbon correlation data, topographic and geomorphological data, land use data, and basic low-carbon attribute data are obtained within the plateau lake basin area. Using preset ecological sensitivity evaluation standards, low-carbon sensitivity evaluation standards, and minimum evaluation units as analysis conditions, spatial analysis methods are employed to comprehensively analyze the topographic data, land use data, and low-carbon attribute basic data to obtain ecologically sensitive areas and low-carbon key areas.

3. The method for assessing the digital ecological composite low-carbon value of plateau lakes according to claim 2, characterized in that, Obtain environmental characteristic data and low-carbon attribute data of the ecologically sensitive area. Based on the environmental characteristic data, low-carbon attribute data, and the requirements for ecological protection-low-carbon synergy, determine several digital ecological monitoring points, including: Based on the topographic data, land use data, and low-carbon attribute data, spatial interpolation methods are used to generate spatial distribution maps of environmental characteristics and low-carbon attributes for the ecologically sensitive areas and low-carbon key areas. The environmental characteristic data includes water quality parameters, biodiversity indicators, and vegetation cover, while the low-carbon attribute data includes soil carbon storage, water carbon flux, and vegetation carbon sequestration capacity. Based on the spatial distribution map of environmental characteristics and the spatial distribution map of low-carbon attributes, calculate the coefficient of variation of environmental characteristics, spatial autocorrelation index, coefficient of variation of low-carbon attributes, and low-carbon spatial correlation index within the ecologically sensitive area. Remote sensing image data, ecological vulnerability index, and low-carbon vulnerability index of the ecologically sensitive area and low-carbon key area are acquired, and normalized vegetation index and vegetation carbon sink potential index are calculated based on the remote sensing image data. Based on the environmental characteristic variation coefficient, the spatial autocorrelation index, the normalized vegetation index, the ecological vulnerability index, the low-carbon attribute variation coefficient, the low-carbon spatial correlation index, the vegetation carbon sink potential index, and the low-carbon vulnerability index, a monitoring site suitability evaluation matrix is ​​constructed, and the monitoring suitability score of different locations in the region is calculated. Based on the distribution of human activities, several digital ecological monitoring points that meet the requirements of ecological protection-low-carbon synergy are selected from several locations whose monitoring suitability scores are greater than or equal to the monitoring suitability score threshold. The requirements of ecological protection-low-carbon synergy include: the distance between the monitoring point and any source of human activity interference is greater than a preset protection distance; the carbon sink potential of the monitoring point is not less than a preset threshold; the distance between the monitoring point and the boundary of its adjacent ecologically sensitive area / low-carbon key area is within a preset reasonable range; and the spacing between the monitoring point and its adjacent monitoring points is greater than a preset monitoring spacing.

4. The method for assessing the digital ecological composite low-carbon value of plateau lakes according to claim 3, characterized in that, Based on the preset ecosystem service-compound low-carbon synergistic assessment indicators and the distribution of human activities in the area where the plateau lake is located, several core monitoring points for the ecosystem service-compound low-carbon synergistic value were selected from several digital ecological monitoring points, including: Based on the location information of several digital ecological monitoring points and the ecosystem service-composite low-carbon synergistic assessment indicators, an ecological-low-carbon synergistic impact assessment path is generated. Based on the preset assessment distance, obtain several assessment sampling points along the ecological-low-carbon synergistic impact assessment path; Based on the preset assessment radius and impact weight, an ecological-low-carbon synergistic impact assessment area is established at each of the assessment sampling points; Obtain the overlapping area between the ecological-low-carbon synergistic impact assessment area and the distribution of human activities, and determine the degree of impact on ecosystem services and the degree of impact on low-carbon value based on the overlapping area; Based on the degree of impact on ecosystem services, the degree of impact on low-carbon value, and the weight allocation of the ecosystem service-composite low-carbon synergistic assessment indicators corresponding to each of the aforementioned ecosystem-low-carbon synergistic impact assessment paths, the comprehensive index of ecosystem-low-carbon synergistic services corresponding to each of the aforementioned ecosystem-low-carbon synergistic impact assessment paths is determined. Based on the digital ecological monitoring points corresponding to each of the aforementioned ecological-low-carbon synergistic impact assessment paths, the comparison results between the comprehensive ecological-low-carbon synergistic service index and the preset ecological-low-carbon synergistic service index threshold are used to select core monitoring points from a number of digital ecological monitoring points; among them, the digital ecological monitoring points corresponding to the ecological-low-carbon synergistic impact assessment paths where the comprehensive ecological-low-carbon synergistic service index is greater than the ecological-low-carbon synergistic service index threshold are the core monitoring points.

5. The method for assessing the digital ecological composite low-carbon value of plateau lakes according to claim 4, characterized in that, Based on the location information of several digital ecological monitoring points and the ecosystem service-composite low-carbon synergistic assessment indicators, an ecological-low-carbon synergistic impact assessment path is generated, including: Based on the location information of several digital ecological monitoring points and the ecosystem service-composite low-carbon synergistic assessment index, a network analysis algorithm is used to generate an initial assessment path point sequence starting from each of the digital ecological monitoring points. Based on preset path intervals, curve smoothness, minimum turning angle and maximum slope limits, and low-carbon value continuity requirements, the initial assessment path point sequence is connected to generate an ecological-low-carbon synergistic impact assessment path.

6. The method for assessing the digital ecological composite low-carbon value of plateau lakes according to claim 5, characterized in that, Calculate the ecosystem service-composite low-carbon synergistic value index corresponding to each of the aforementioned core monitoring sites, including: Based on each of the core monitoring points, the ecological-low-carbon collaborative assessment area of ​​the plateau lake is determined; the ecological-low-carbon collaborative assessment area is divided into several assessment grid units using a grid of preset size; Based on the type of ecosystem service in each assessment grid cell and the area of ​​each assessment grid cell, the ecosystem service density and low-carbon service density of each assessment grid cell are determined, and assessment grid cells with ecosystem service density and low-carbon service density greater than a preset density threshold are designated as key assessment areas. A radial assessment grid is established at the core monitoring points within the key assessment area, and several value assessment points are generated on the radial assessment grid. Based on the distribution of human activities, the service supply and demand relationship between the value assessment points and each assessment grid unit within the key assessment area is obtained, and several effective assessment points are selected from the several value assessment points. Based on the ecosystem service value, low-carbon value, and total number of the effective assessment points, determine the ecosystem service-composite low-carbon synergistic value index corresponding to each of the core monitoring points.

7. The method for assessing the digital ecological composite low-carbon value of plateau lakes according to claim 6, characterized in that, Based on the location information of several core monitoring points, and taking the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the center, a spatial interpolation method is used to generate an ecosystem service-composite low-carbon synergistic value assessment surface, including: Based on the location information of several core monitoring points, taking the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the center, an initial ecosystem-low-carbon synergistic value point sequence is generated using a spatial interpolation method. Based on the preset spatial resolution, interpolation accuracy requirements, and low-carbon value interpolation priority, the value of each point in the initial ecological-low-carbon synergistic value point sequence is adjusted to obtain an optimized ecological-low-carbon synergistic value point sequence. Based on the preset spatial continuity constraints, interpolation radius, interpolation accuracy requirements, and low-carbon value spatial distribution constraints, the optimized ecological-low-carbon synergistic value point sequence is processed to obtain the ecosystem service-composite low-carbon synergistic value assessment surface.

8. The method for assessing the digital ecological composite low-carbon value of plateau lakes according to claim 7, characterized in that, Calculate the spatial coverage of the ecosystem services-complex low-carbon synergistic value assessment surface, including: Based on the location information of several core monitoring points, the scope of the ecological-low-carbon collaborative assessment of the plateau lake is determined; Based on the preset assessment accuracy and ecological-low-carbon value stratification standard, several value level regions corresponding to the ecosystem service-composite low-carbon synergistic value assessment surface are generated. Based on the location information of each value level region, the preset assessment credibility threshold and the low-carbon assessment credibility threshold, the effective assessment area corresponding to the ecosystem service-composite low-carbon synergistic value assessment surface is determined. The spatial coverage of the ecosystem service-composite low-carbon synergistic value assessment surface is obtained by comparing the area of ​​the overlapping area between the effective assessment area and the ecological-low-carbon synergistic assessment range with the area of ​​the ecological-low-carbon synergistic assessment range.

9. The method for assessing the digital ecological composite low-carbon value of plateau lakes according to claim 8, characterized in that, The method further includes: When the spatial coverage is less than the preset coverage threshold, the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index will be removed. A new ecosystem service-composite low-carbon synergistic value assessment surface is generated, centered on the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index. The spatial coverage of the new ecosystem service-composite low-carbon synergistic value assessment surface is calculated until the spatial coverage meets the coverage threshold.

10. A digital ecological composite low-carbon value assessment system for plateau lakes, applicable to the digital ecological composite low-carbon value assessment method for plateau lakes as described in any one of claims 1-9, characterized in that, include: The data identification module is used to identify the ecologically sensitive areas and low-carbon key areas of the plateau lakes based on the geographical environment data and composite low-carbon correlation data of the plateau lake area. The location determination module is used to acquire environmental characteristic data and low-carbon attribute data of the ecologically sensitive area, and determine several digital ecological monitoring locations based on the environmental characteristic data, low-carbon attribute data and ecological protection-low-carbon synergy requirements. The site selection module is used to select several core monitoring sites for the synergistic value of ecosystem services and low carbon based on preset ecosystem service-composite low carbon synergy assessment indicators and the distribution of human activities in the area where the plateau lake is located. The value assessment module is used to calculate the ecosystem service-composite low-carbon synergistic value index corresponding to each of the core monitoring points; based on the location information of several core monitoring points, taking the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the center, the module uses a spatial interpolation method to generate an ecosystem service-composite low-carbon synergistic value assessment surface, and calculates the spatial coverage of the ecosystem service-composite low-carbon synergistic value assessment surface. The location determination module is used to determine the core monitoring point with the highest current ecosystem service-composite low-carbon synergistic value index as the main evaluation benchmark point when the spatial coverage is greater than or equal to a preset coverage threshold.

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